System and method for augmenting search results

ABSTRACT

Systems and methods are provided to augment the search results of a search operation are provided. The method enhances a user&#39;s experience by identifying and displaying information within the search results which is of a remarkable value. Such information may be presented with a different presentation semantics from the rest of the search result. Such presentation semantics being indicative of the remarkability of the information.

CROSS REFERENCE TO RELATED APPLICATION

This application claims priority to U.S. Provisional Application Ser.No. 61/950,253 entitled Search Results Display filed on Mar. 10, 2014,which is incorporated herein by reference.

TECHNICAL FIELD

The present disclosure generally relates to search engine operations andmethods to display the results of a search operation. Particularly, thedisclosure relates to a system and method for augmenting the results ofa search operation by identifying for the user information in theresults that is of a remarkable nature.

BACKGROUND

The statements in this section merely provide background informationrelated to the present disclosure and may not constitute prior art.

It is commonly required in the field of Information Technology toprovide a service that searches through data sources. The data sourceherein may refer to data and/or document(s) on the Internet, intranet,storage devices, and so on. In order to use a search engine, a userseeking information on a desired topic generally inputs a search queryconsisting of keyword(s) or phrase(s) relevant to the topic into thesearch interface of the search engine. In response, the search enginetypically displays a report with a prioritized list of links pointing torelevant documents containing the search keywords. Oftentimes, a shortsummary of text i.e., extract/snippet is also included for each result.The extract/snippet is that portion or portions of the text in thedocument that contain the keywords from the search query. In addition,to facilitate easy understanding of the search results, the keyword(s)from the search query contained in the extracts may be highlighted.

US 20120150861 A1 disclosed a method of identifying answers to searchqueries and highlighting the answers when they appear in search results.This is however limited to the answers in the snippet merely to directthe user's attention to the answers.

While highlighting the keywords and answers in search results ishelpful, it is not sufficient in fully understanding the search results.A drawback in such limited highlighting in the search results is that itdoes not help the user in understanding the significance of theinformation in the search results, thereby making the results lessuseful to the user.

Another drawback of the existing search results is that it takes theuser considerable amount of time and effort to understand the foundresults. There are no clues in the search results which will help theuser to quickly identify remarkable information within the searchresults.

In view of the above drawbacks, there remains a need for an effectivemethod of searching data sources for useful information relating totopics of interest.

SUMMARY

The following presents a simplified summary of the disclosure in orderto provide a basic understanding to the reader. This summary is not anextensive overview of the disclosure and it does not identifykey/critical elements of the disclosure or delineate the scope of thedisclosure. Its sole purpose is to present some concepts disclosedherein in a simplified form as a prelude to the more detaileddescription that is presented later.

The present disclosure generally relates to methods and systems forsearching data sources for information. Particularly, the inventionrelates to a computer implemented method of augmenting the searchresults in a multi-document search environment, said method comprising(a) Identifying remarkable data (a) Predefining identification rules forsaid remarkable data (c) Storing in a storage unit at least one suchidentification rule; wherein the identification rule comprisesattributes selected from the group comprising a key, a value,classification, clarification and combinations thereof (d) Identifyingat least one such remarkable data within the search results (e)highlighting at least a portion of the remarkable data within the searchresults.

A remarkable data in accordance with the invention is to be interpretedbroadly to include any value associated with a key that is of aremarkable nature as determined by the system. The classificationattribute in the identification rule identifies the type of suchremarkable data and may be selected from the group comprising a goodvalue, a bad value, a record, and combinations thereof. Theclarification attribute in the identification rule gives additionalinformation regarding the remarkable data.

In one embodiment of the invention, the remarkable data within thesearch results are highlighted based on the identification rule. In apreferred embodiment, the remarkable data within the search results ishighlighted based on the classification attribute of the identificationrule.

Depending on the classification, different presentation semantics couldbe applied to the remarkable data. The presentation semantics selectedfrom the group comprising font color, font size, font weight, fontfamily, text decorations, borders, shading and combinations thereof.

In another embodiment, the clarification attribute is appended to thesearch result. The clarification attribute is appended to the searchresult by a graphical user interface element. In a preferred embodiment,wherein the graphical user interface element is a tool tip.

In a preferred embodiment of the present invention, remarkable data withsimilar classification attributes are presented with similarpresentation semantics across all search results.

In another aspect of the present disclosure is provided with a systemcomprising search engine unit. The search engine unit may comprise oneor more logics configured to perform the functions and operationsassociated with the above-disclosed methods.

In another aspect of the present disclosure is provided a computerprogram product executable in a memory of a search engine unit

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings described herein are for illustration purposes only and arenot intended to limit the scope of the present disclosure in anyway.Throughout the disclosure, like elements are represented by likereference numerals, which are given by way of illustration only and thusare not limitative of the various embodiments.

Other objects and advantages of the present disclosure will becomeapparent to those skilled in the art upon reading the following detaileddescription of the preferred embodiments, in conjunction with theaccompanying drawings, wherein:

FIG. 1 is a block diagram illustrating an exemplary search environmentin accordance with an embodiment of the present disclosure.

FIG. 2 is a block diagram of an exemplary computing device of FIG. 1.

FIG. 3 depicts exemplary rules for the identification of remarkabledata.

FIG. 4 depicts exemplary rules for highlighting remarkable data.

FIG. 5 depicts an exemplary search operation illustrating identifyingand highlighting remarkable data in accordance with the presentdisclosure.

FIG. 6 is a flow diagram of a method of displaying search resultscomprising highlighting of remarkable data in accordance with one ormore embodiments.

DETAILED DESCRIPTION

It is to be understood that the present disclosure is not limited in itsapplication to the details of construction and the arrangement ofcomponents set forth in the following description or illustrated in thedrawings. The present disclosure is capable of other embodiments and ofbeing practiced or of being carried out in various ways. Also, it is tobe understood that the phraseology and terminology used herein is forthe purpose of description and should not be regarded as limiting.

The use of “including”, “comprising” or “having” and variations thereofherein is meant to encompass the items listed thereafter and equivalentsthereof as well as additional items. The terms “a” and “an” herein donot denote a limitation of quantity, but rather denote the presence ofat least one of the referenced item. Further, the use of terms “first”,“second”, and “third”, and the like, herein do not denote any order,quantity, or importance, but rather are used to distinguish one elementfrom another.

The disclosure described here is equally applicable to searching andreturning links to any document containing text and optionalpresentation semantics (the look and feel instructions) such as, but notlimited to, HTML, DHTML, XML, SGML, PDF, E-mail, Microsoft® Worddocuments, Microsoft® Power point documents, news group postings,multimedia objects, Graphics Interchange Format images and/or ShockwaveFlash files.

Through the length of the specification and claims, the words “extract”and “snippet” are used interchangeably.

FIG. 1 depicts a search environment 100 in accordance with an exemplaryembodiment of the present disclosure. It will be understood andappreciated by those of ordinary skill in the art that the computingsystem architecture 100 shown in FIG. 1 is merely an example of onesuitable computing system and is not intended to suggest any limitationas to the scope of use or functionality of the present invention.Neither should the computing system architecture 100 be interpreted ashaving any dependency or requirement related to any singlemodule/component or combination of modules/components illustratedtherein.

The system 100 comprises a search engine unit 110, a client 120 and astorage unit 140. The search engine unit 110, the client 120 and thestorage unit 140 all communicate over a network 130.

The network 130 can include any type of network known in the art orfuture-developed. In this regard, the network 130 may be an Ethernet, alocal area network (LAN), or a wide area network (WAN), e.g., theInternet, or a combination of networks.

The search engine unit 110 may be a dedicated or shared server includingbut not limited to any type of application server, database server, orfile server configurable and combinations thereof. The search engineunit 110 and the client 120 may include, but are not limited to, acomputer, handheld unit, mobile unit, consumer electronic unit, or thelike.

The exemplary search engine unit 110 comprises search engine logic 111,search result parsing logic 112 and search result highlighting logic113.

In the exemplary search engine unit 110, the search engine logic 111 maybe configured to identify and construct search results for a searchquery.

The search engine unit 110 further comprises the search result parsinglogic 112. The search result parsing logic 112 may be configured toidentify keys and corresponding to each key associated value withinsearch results. The search result parsing logic 112 identifieskey/values by looking at the clues within the search result or cluesfrom the document that the search result is extracted from. The cluesmay include, but not limited to, presentation semantics, format,sentence structure, natural language processing (NLP) of the searchresult text or the search result text in the document.

In addition, the search result parsing logic 112 may be configured toidentify remarkable data among the identified key/values. The process ofidentifying remarkable data is further explained with reference to FIG.3 and FIG. 5.

The remarkable data within the search results identified by the searchresult parsing logic 112 may be highlighted and augmented by the searchresult highlighting logic 113.

The storage unit 140 is configured to store information associated withsearch results, remarkable data identification rules, highlightingrules, or the like. In various embodiments, such information mayinclude, without limitation, domains, URLs, webpages, websites, indexes,identification rules, highlighting rules, information associatedtherewith, and the like. In embodiments, the storage unit 140 isconfigured to be searchable for one or more of the items stored inassociation therewith. It will be understood and appreciated by those ofordinary skill in the art that the information stored in associationwith the storage unit 140 may be configurable and may include anyinformation relevant to search results and highlighting of remarkabledata, or the like. The content and volume of such information are notintended to limit the scope of embodiments of the present disclosure inany way. Further, though illustrated as a single, independent component,the storage unit 140 may, in fact, be a plurality of storage units, forinstance a database cluster, portions of which may reside on the searchengine unit 110, the client 120, another external computing device (notshown), and/or any combination thereof. The single unit depictions aremeant for clarity, not to limit the scope of embodiments in any form.

A user 122 through the client logic 121 on the client 120 may enter asearch query consisting of keyword(s) which may identify the type ofinformation that the user is interested in retrieving. The client logic121 may comprise, for example, an Internet browser; however, other typesof client logic 121 for interfacing with the user 122 and forcommunicating with the search engine unit 110 may be used in otherembodiments of the present disclosure. The client logic 121 transmitsthe user search query to the search engine unit 110 via the network 130.Upon receiving the user search query the search engine unit 110 examinesthe storage unit 140 and compiles a prioritized list of search resultswith remarkable data within the search results highlighted and returnsthe search results to the client logic 121 which displays the results tothe user 122 in a window.

In some preferred embodiments, the search engine unit 110 is shown inFIG. 2. It should be noted, however, that embodiments are not limited toimplementation on such computing devices, but may be implemented on anyof a variety of different types of computing units within the scope ofembodiments hereof. The search engine unit 110 (as shown in FIG. 1) isonly one example of a suitable computing/search environment and it isnot intended to suggest any limitation as to the scope of use orfunctionality of the disclosure.

In some embodiments, the search engine unit 110 may include a bus 206, aprocessor 201, memory 202, network device 203, input device 204, and anoutput device 205. Bus 206 may include a path that permits communicationamong the components of the search engine unit 110.

The memory 202 stores the search engine logic 111, the search resultparsing logic 112, and the search result highlighting logic 113 assoftware in memory 202.

The memory 202 may be any type of computer memory known in the art orfuture-developed for electronically storing data and/or logic, includingvolatile and non-volatile memory. In this regard, memory 202 can includerandom access memory (RAM), read-only memory (ROM), flash memory, anymagnetic computer storage unit, including hard disks, floppy discs, ormagnetic tapes, and optical discs.

The processor 201 comprises processing hardware for interpreting orexecuting tasks or instructions stored in memory 202. Note that theprocessor 201 may be a microprocessor, a digital processor, or othertype of circuitry configured to run and/or execute instructions.

The network device 203 may be any type of network unit (e.g., a modem)known in the art or future-developed for communicating over a network130 (FIG. 1). In this regard, the search engine unit 110 (FIG. 1)communicates with the storage unit 140 (FIG. 1) and the client 120(FIG. 1) over the network 130 (FIG. 1) via the network device 203.

The input device 204 is any type of input unit known in the art orfuture-developed for receiving data. As an example, the input unit 204may be a keyboard, a mouse, a touch screen, a serial port, a scanner, acamera, or a microphone.

The output device 205 may be any type of output unit known in the art orfuture-developed for displaying or outputting data. As an example, theoutput device 205 may be a liquid crystal display (LCD) or other type ofvideo display unit, a speaker, or a printer.

Note that the disclosure may also be practiced in a distributedcomputing environment where tasks or instructions of search engine unit110 (FIG. 1) are performed by multiple computing units communicativelycoupled to the network.

Further note that, the search engine unit 110 (FIG. 1) components may beimplemented by software, hardware, firmware or any combination thereof.In the exemplary search engine unit 110, depicted by FIG. 1, all thecomponents are implemented by software and stored in memory 202.

FIG. 3 depicts a portion of exemplary identification rules 300 stored inthe storage unit 140 (FIG. 1) and made available to the search engineunit 110 (FIG. 1) to identify remarkable data within the search results.

The identification rules 300 comprise of keys and corresponding to eachkey a value. For each key and value combination in identification rules300, there may be optional additional information which may furtherclassify and clarify identified remarkable data.

An identification rule in 300 may identify and narrowly classify datainstead of a broad classification. For example, an identification rulemay identify data as remarkable data and narrowly classify as excellent,very good, good, etc. instead of a broad classification as good. Anotheridentification rule may identify data as remarkable data and narrowlyclassify as world record, national record, regional record etc., insteadof a broad classification as record.

Exemplary identification rule 301 comprises of key “ODI Score” and thecorresponding value “50-100”. This key/value combination represents arange of values between “50” and “100”. This rule may identify any ODIscore value between “50” and “100” in text as remarkable data with “Bad”classification and “Low Score” as the clarification for theidentification.

Exemplary identification rule 304 comprises of key “Loreum IpsumPopulation” and the corresponding value “45 million”. This rule mayidentify Loreum Ipsum population value in text as remarkable data with“World Record” classification and “Top Ranked City In Terms ofPopulation” as the clarification for the identification.

Exemplary identification rule 306 comprises of key “Award” and thecorresponding value “Medal of Honor”. This rule may identify any awardwith value medal of honor in text as remarkable data with “Excellent”classification and the “US Highest Military Honor” as the clarificationfor the identification.

Note that the identification rules 300 may be compiled manually orcompiled automatically by parsing data sources using NLP techniquesknown in the art.

In the exemplary embodiment of the present disclosure, each remarkabledata in search results may be presented to the user in differentpresentation semantics based on the remarkable data classification. Inthis regard, presentation semantics rules for each classification may bestored in the storage unit 140 (FIG. 1).

FIG. 4 shows a portion of exemplary presentation semantics rules 400that may be applied for various classifications. From the presentationsemantics rules 400, remarkable data classified as “Bad” may be shown inred color. Thus, remarkable data identified by the identification rules301 and 302 (FIG. 3) may be shown in red color.

Note that the presentation semantics may not be limited to font colorand text decoration. In other embodiments, presentation semantics mayinclude, but not limited to, font weight, font family, background color,borders, shading etc.

Note that in other embodiments, all or some of the classifications mayshare the same presentation semantics.

FIG. 5 depicts a GUI 500 with a portion of search results that isdisplayed to the user 122 (FIG. 1) by the client logic 121 (FIG. 1) withremarkable data highlighted as a result of the user searching forkeywords “Loreum Ipsum” 501.

Upon receiving the search query 501, the search engine logic 111(FIG. 1) compiles a list of search results from the storage unit 140(FIG. 1). One such result 502 is shown in the GUI 500. Within the searchresult 502, the search result parsing logic 112 (FIG. 1) identifies“Population” 504 as a key and “44.89 million” 505 as its correspondingvalue based on the sentence structure where these two words areseparated by a “:”. In this example, the search result parsing logic 112(FIG. 1) identifies the word before “:” as the key and the word after“:” as the value. However, when the search result parsing logic 112(FIG. 1) tries to match the key “Population” 504 found in search result502 with a key from the identification rules 300 (FIG. 3), no match isfound. The search result parsing logic 112 (FIG. 1) then parses thetitle 503 using NLP and finds two nouns “City” and “Loreum Ipsum” andsearches identification rules 300 (FIG. 3) for a matching key byappending each noun to the key “Population” 504. The key ofidentification rule 304 (FIG. 3) matches the combination “Loreum Ipsum”and “Population”. Since broad classification for rule 304 is record, novalue comparison is necessary and the key 504 value 505 is identified asremarkable data by the identification rule 304 (FIG. 3).

Key “Air Quality Index” 506 and the corresponding value “900” 507 arematched to the identification rule 303 (FIG. 1). In this case, thesearch result parsing logic 112 (FIG. 1) finds the match based on boththe key and the value combination. The key “Air Quality Index” 506 is anexact match to the identification rule 303 key and the value “900” 507matches the value criteria of “>800” in the identification rule 303.Hence, this key/value pair is identified as remarkable data with aclassification of “Very Bad”.

Similarly, key “Literary Index” 508 and corresponding value “89” 509 isidentified as remarkable data by the identification rule 305 and theclassification is “Very Good”.

Each key/value pair in the search result 502 is considered remarkabledata if at least one matching identification rule is identified by thesearch result parsing logic 112 (FIG. 1).

Note that for some of the key/value pairs in search results no matchingkey(s) may be found in identification rules 300 (FIG. 3). Hence, thesekey/value pairs will not be considered remarkable data.

Note that the search result parsing logic 112 (FIG. 1) may understandall the variations for a key. For example, the search result parsinglogic 112 (FIG. 1) may recognize “Population of Loreum Ipsum” and“Population Loreum Ipsum” as “Loreum Ipsum Population”. In anotherembodiment, all the variations may be stored in storage unit 140(FIG. 1) and made available to the search result parsing logic 112 (FIG.1).

For each remarkable data identified by the search result parsing logic112 (FIG. 1) in the search result 502, the search result highlightinglogic 113 (FIG. 1) identifies the classification from the correspondingmatching identification rule. Based on the classification, the searchresult highlighting logic 113 (FIG. 1) identifies a highlighting ruleand applies the presentation semantics from the highlighting rule to theremarkable data in the search result 502.

Key “Population” 504 and value “44.89 million” 505 is classified as“World Record” in its corresponding matching identification rule 304(FIG. 3). Based on the “Word Record” classification, the search resulthighlighting logic 113 (FIG. 1) identifies highlighting rule 403 (FIG.4) and applies presentation semantics of the highlighting rule 403 (FIG.4) to the remarkable data value 505. Note that in GUI 500 the color ofthe remarkable data value 505 is orange and is underlined.

Similarly, for Key “Air Quality Index” 506 and value “900” 507 isclassified as “Very Bad” in its corresponding matching identificationrule 303 (FIG. 3). Based on the “Very Bad” classification, the searchresult highlighting logic 113 (FIG. 1) identifies highlighting rule 401(FIG. 4) and applies presentation semantics of the highlighting rule 401(FIG. 4) to the remarkable data value 507. Note that in GUI 500 thecolor of the remarkable data value 507 is dark red.

For key “Literacy Index” 508 and value “89” 509 is classified as “VeryGood” in its corresponding matching identification rule 305 (FIG. 3).Based on the “Very Good” classification, the search result highlightinglogic 113 (FIG. 1) identifies highlighting rule 402 (FIG. 4) and appliespresentation semantics of the highlighting rule 402 (FIG. 4) to theremarkable data value 509. Note that in GUI 500 the color of theremarkable data value 509 is dark blue.

Note that in other embodiments the presentation semantics may be appliedto both keys and values. In yet another embodiment the presentationsemantics may be applied only to keys.

Note that in those cases where clarifications for identification rulesare available, the search result highlighting logic 113 (FIG. 1) mayappend the clarifications from the remarkable data identification rulesto the search results containing the remarkable data. In the exemplaryembodiment, the search result highlighting logic 113 (FIG. 1) appendsclarification attribute of the identification rule for the remarkabledata to the value of the remarkable data by the tool tip graphical userinterface element. Thus, when the user moves the cursor over theremarkable data value 505, the identification rule 304 (FIG. 3)clarification attribute pops up on the GUI 500 next to the remarkabledata value 505.

In one embodiment, a legend may be included in the GUI 500 to indicatethe presentation semantics associated with each classification.

FIG. 6 is a flow chart illustrating one method in accordance with thepresent disclosure. In step 601, the search engine unit 110 (FIG. 1) mayaccept the search query comprising of keyword(s)/search term(s). In step602, the search engine unit 110 (FIG. 1) may find search resultsmatching search query criteria. For each search result, steps 603 and604 may be performed by the search engine unit 110 (FIG. 1). In step603, the search result parsing logic 112 (FIG. 1) may identifyremarkable data within the search result text with the aid ofidentification rules. In step 604, the search result highlighting logic113 (FIG. 1) for each remarkable data in the search result identifieshighlighting rule based on the classification of the remarkable data andapplies presentation semantics from the highlighting rule to theremarkable data. In step 605, the search results with remarkable datahighlighted may be returned.

The claimed subject matter has been provided here with reference to oneor more features or embodiments. Those skilled in the art will recognizeand appreciate that, despite of the detailed nature of the exemplaryembodiments provided here, changes and modifications may be applied tosaid embodiments without limiting or departing from the generallyintended scope. These and various other adaptations and combinations ofthe embodiments provided here are within the scope of the disclosedsubject matter as defined by the claims and their full set ofequivalents.

1. A computer implemented method of augmenting the search results in amulti-document search environment, said method comprising (a)Identifying remarkable data (b) Predefining identification rules forsaid remarkable data (c) Storing in a storage unit at least one suchidentification rule; wherein the identification rule comprisesattributes selected from the group comprising a key, a value,classification, clarification and combinations thereof (d) Identifyingat least one such remarkable data within the search results (e)Highlighting at least a portion of the remarkable data within the searchresults.
 2. A method as in claim 1, wherein the classification attributeis selected from the group comprising a good value, a bad value, arecord, and combinations thereof.
 3. A method as in claim 2, wherein thehighlighting of the remarkable data on the search result page is basedon the identification rule.
 4. A method as in claim 3 wherein thehighlighting of the remarkable data on the search result page is basedon the classification attribute of the identification rule.
 5. A methodas in claim 4, wherein the presentation semantics for highlighting ofremarkable data on the search result page is selected from the groupcomprising font color, font size, font weight, font family, textdecorations, borders, shading and combinations thereof.
 6. A method asin claim 5, wherein the presentation semantics are uniform for datahaving similar classification attributes.
 7. A method as in claim 1,wherein the clarification attribute of the identification rule for theremarkable data is appended to the search result.
 8. A method as inclaim 7, wherein the clarification attribute of the identification rulefor the remarkable data is appended to the remarkable data of the searchresult by a graphical user interface element.
 9. The method as in claim8, wherein the graphical user interface element is a tool tip.
 10. Asearch system, comprising: one or more servers; and logic configured toreceive a search query and prepare a list of search results matching thesearch query criteria, the logic further configured to identifyremarkable data within the search results with the aid of identificationrules, the logic further configured to identify highlighting rule basedon the classification of the remarkable data and apply the presentationsemantics from the highlighting rule to the remarkable data and returnsearch results with remarkable data highlighted.
 11. A system as inclaim 10, wherein the classification attribute is selected from thegroup comprising a good value, a bad value, a record, and combinationsthereof.